private void runSingleLearningStep()
{
if (!valuesOK)
{
checkVariables();
}
if (valuesOK && !checkIfCurrentEpochIsCorrect())
{
if (currentIteration >= amountOfLearningPoints)
{
currentIteration = 0;
currentIterationsInEpoch.Clear();
scatterSeriesAbove.Points.Clear();
scatterSeriesBelow.Points.Clear();
plotModel.InvalidatePlot(true);
}
SingleIteration iterationResult = new SingleIteration();
iterationResult.inputs = new int[3];
iterationResult.inputs[0] = 1;
iterationResult.inputs[1] = learningSet[currentIteration, 0];
iterationResult.inputs[2] = learningSet[currentIteration, 1];
iterationResult.weights = new double[3];
iterationResult.weights[0] = weights[0];
iterationResult.weights[1] = weights[1];
iterationResult.weights[2] = weights[2];
setIterationsExpectedResult(ref iterationResult);
for (int i = 0; i < 3; i++)
{
iterationResult.sumResult += iterationResult.inputs[i] * iterationResult.weights[i];
}
iterationResult.sumResult = Math.Round(iterationResult.sumResult, 3);
iterationResult.uniPolarResult = iterationResult.sumResult > 0 ? 1 : 0;
iterationResult.isOK = iterationResult.uniPolarResult == iterationResult.expectedResult;
if (!iterationResult.isOK)
{
updateWeights(iterationResult);
}
currentIterationsInEpoch.Add(iterationResult);
iterationHistory.Add(iterationResult);
currentIteration++;
displayCurrentEpochCheckedPoints();
}
}
private void updateWeights(SingleIteration iterationValues)
{
autoUpdate = true;
IEnumerable <TextBox> weightsTextBoxes = weightsGrid.Children.OfType <TextBox>();
for (int i = 0; i < 3; i++)
{
weights[i] = weights[i] + (learningCoefficient * (iterationValues.expectedResult - iterationValues.uniPolarResult) * iterationValues.inputs[i]);
weightsTextBoxes.ElementAt(i).Text = weights[i].ToString();
}
autoUpdate = false;
}
private void setIterationsExpectedResult(ref SingleIteration singleIteration)
{
singleIteration.expectedResult = (singleIteration.inputs[2] > (separatingFunctionA * singleIteration.inputs[1] + separatingFunctionB)) ? 1 : 0;
}
